In most studies, disadvantaged populations experienced above-average losses. As anticipated, losses were frequently greater in mathematics (3 months) than in reading (one-and-a-half months). School closures in the second quarter of 2020 put students typically 2 to 3 months behind the academic milestones their cohorts would be expected to reach. Subsequent studies reporting pre- and post-school closure assessment data suggest losses were not as great as some of the most pessimistic projections, although the overall pattern predicted was correct. These events include normal variations in teaching time, sickness absence, weather-related school closures, teacher strikes, natural disasters, previous pandemics, and the aforementioned summer learning loss.Įarly modelling of the impact on learning of school closures projected average learning losses, with greater losses in mathematics than reading, and an uneven distribution of losses according to socio-economic factors. In addition to this, we review the diverse literature on the impact of other – non-COVID-19-related – events on students’ attainment. In the first of 2 main sections of this report, we review the early papers that modelled the impact of school closures on students’ attainment and more recent reports based on students’ performance in large-scale testing programmes following school closures. This represents, at best, no progress and, at worst, regression for the worst-affected students.
The third scenario is much like the second, except that a significant proportion of students score zero – or very close to it – on their assessments, producing a second peak at the low end of the distribution curve. Some students may do better than they would otherwise have done, some may be relatively unaffected, but many will do worse: some of them quite substantially so. In the second scenario, mean attainment falls, but the distribution of losses is uneven across the student population, causing the standard deviation to increase. This means that any losses would be distributed evenly across the student population, that is all students would be affected equally. In the first scenario, mean attainment falls however, the overall distribution of attainment remains the same. Three scenarios for learning loss were identified from the literature. The purpose of this report is to review international research papers and reports that may help our understanding of the scale and nature of learning loss in England. Modelling based on data pertaining to ‘summer learning loss’ suggested that students might learn little to nothing while schools remain closed, and studies of the efficacy of remote – including online – learning suggested it may only partially offset the losses. Rapid evidence assessments published at the beginning of the school closures painted a grim picture of the impact these closures could have on students’ learning. In England, this largely took the form of online learning, up to and including teacher-led lessons. To minimise the learning lost while schools remained closed, governments and schools around the world responded by putting in place remote learning. By the summer (northern hemisphere), when schools in many countries break for holidays, globally, the average student had missed almost 50 school days – or a quarter of a school year.
In early April 2020, at the peak of the closures, 1.6 billion students – over 90% of the world’s total – were thought to be affected. In March 2020, schools around the world began to close as part of a global effort to reduce the transmission of the coronavirus (COVID-19) pandemic.